Linear and Ellipsoidal Restrictions in Linear Regression

作     者：Stahlecker, P.S. Trenkler, G.T. 

作者机构：University of Mainz University of Dortmund Germany 

出 版 物：《Statistics》 (Statistics)

年 卷 期：1991年第22卷第2期

页      面：163-176页

学科分类：07[理学] 070104[理学-应用数学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 

主　　题：Linear regression model minimax estimation prior information quadratic loss functions restricted parameter space 

摘      要：The problem of combining linear and ellipsoidal restrictions in linear regression is investigated. Necessary and sufficient conditions for compactness of the restriction set are proved assuring the existence of a minimax estimator. When the restriction set is not compact a minimax estimator may still exist for special loss functions and regression designs. © 1991, Taylor & Francis Group, LLC. All rights reserved.